Structured-light-based vision systems are widely used for various purposes, such as factory automation for robotic assembly and visual inspection. Illumination strategies in such structured-light-based vision systems have been developed for detecting surface imperfections, separating reflection components, estimating material properties, recovering three-dimensional structure, etc. Such structured-light-based vision systems are frequently preferred over passive vision systems because structured-light-based vision systems are typically more reliable in terms of the information that they can recover.
Structured-light-based vision systems are typically required to handle a wide range of shapes and materials. For instance, a single image of a printed circuit board may include diffuse bodies of electronic components, glossy strips of copper connectors, mirror-like solder joints, and shadows cast by components on each other.
FIG. 1 illustrates an example of challenges faced by such systems. As shown, two objects, a sphere 102 and a cube 104, may be illuminated by a single light stripe 106 of the type used to recover three-dimensional information using triangulation. Assume that sphere 102 is highly specular and that cube 104 is diffuse in reflectance. While the top surface of cube 104 may produce a contiguous light stripe in an image captured by image sensor 108 along which depth can be computed, the specular sphere 102 likely will only produce a single highlight at a point P 110 for which depth can be recovered.
The problem of specularities is even more severe in the case of brightness-based structured light methods, such as phase shifting, where the exact brightness at each point is needed to estimate depth. In this case, even the reflection from point P may be too bright (saturated) to be useful.
FIG. 1 also illustrates a problem of shadows faced by structured-light-based vision systems. As can be seen, a point Q 112 is self-shadowed by sphere 102. Although point Q 112 is unobstructed from the vantage point of image sensor 108, it is dark and hence its depth cannot be computed. The same problem arises with right face 114 of cube 104, which is fully visible to the image sensor but does not receive any of the collimated light.
Accordingly, it is desirable to provide improved structured-light-based vision systems that can better handle specular reflections and/or regions in a scene that would be in shadows in a traditional structured-light-based vision system.